Machine learning tagged posts

Researchers focus AI on Finding Exoplanets

Three young planets in orbit around an infant star known as HD 163296 (Photo credit: NRAO/AUI/NSF; S. Dagnello)

New research from the University of Georgia reveals that artificial intelligence can be used to find planets outside of our solar system. The recent study demonstrated that machine learning can be used to find exoplanets, information that could reshape how scientists detect and identify new planets very far from Earth.

“One of the novel things about this is analyzing environments where planets are still forming,” said Jason Terry, doctoral student in the UGA Franklin College of Arts and Sciences department of physics and astronomy and lead author on the study...

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Will Machine Learning help us find Extraterrestrial Life?

Will machine learning help us find extraterrestrial life?
Examples showing the four types of training data. Credit: Nature Astronomy (2023). DOI: 10.1038/s41550-022-01872-z

Researchers have applied a deep learning technique to a previously studied dataset of nearby stars and uncovered eight previously unidentified signals of interest.

When pondering the probability of discovering technologically advanced extraterrestrial life, the question that often arises is, “if they’re out there, why haven’t we found them yet?” And often, the response is that we have only searched a tiny portion of the galaxy. Further, algorithms developed decades ago for the earliest digital computers can be outdated and inefficient when applied to modern petabyte-scale datasets...

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Teaching Photonic Chips to ‘Learn’

CHIP used in research
Silicon Photonic Architecture for Training Deep Neural Networks with Direct Feedback Alignment, OPTICA

A multi-institution research team has developed an optical chip that can train machine learning hardware.

Machine learning applications skyrocketed to $165B annually, according to a recent report from McKinsey. But, before a machine can perform intelligence tasks such as recognizing the details of an image, it must be trained. Training of modern-day artificial intelligence (AI) systems like Tesla’s autopilot costs several million dollars in electric power consumption and requires supercomputer-like infrastructure. This surging AI “appetite” leaves an ever-widening gap between computer hardware and demand for AI...

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A Possible Game Changer for Next Generation Microelectronics

Multicolor patterns of arrows in pointing across, down. (Image by Argonne National Laboratory.)
Magnetic fields created by skyrmions in two-dimensional sheet of material composed of iron, germanium and tellurium. (Image by Argonne National Laboratory.)

Researchers have discovered new properties of tiny magnetic whirlpools called skyrmions. Their pivotal discovery could lead to a new generation of microelectronics for memory storage with vastly improved energy efficiency in high performance computers.

Magnets generate invisible fields that attract certain materials. A common example is fridge magnets. Far more important to our everyday lives, magnets also can store data in computers. Exploiting the direction of the magnetic field (say, up or down), microscopic bar magnets each can store one bit of memory as a zero or a one — the language of computers.

Scientists at the U.S...

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